Jari van Diermen

I am an aspiring bioinformatician driven by a strong interest in using computational
approaches to tackle complex biological problems and generate societal impact.
I seek to pursue this goal by developing and applying innovative computational tools.

As a PhD candidate (2026/03 - 2024/09), I conducted research to better understand the fundamental principles of genome regulation during development. This taught me how to process, analyze and present large amounts of genomics data in HPC environments. Moreover, I developed pipelines for preprocessing multimodal genomics data and an Accompanying R-package, both of which aid the lab in its research efforts.

As a research assistant (2024/03 - 2023/07), I improved the computational pipeline for evolutionary inference with improved parallelization, data cleaning, documentation and Docker containerization for reproducibility. Additionally, I developed a data dashboard using R shiny to improve exploration of the pipeline results. This allowed me to further improve my Python, R and Bash programming expertise.

As a research intern (2023/03 - 2022/05), I have created a computational pipeline that uses evolutionary inference to better predict which genes are relevant for the regenerative wound-healing in the African Spiny mice. I gained extensive experience in high performance computing (SLURM), programming (R, Python and Bash) and version control (Git, Github). Additionally, I learned to present and report my findings.

I obtained a Bachelor’s degree in Biology (cum laude) and a Master’s degree in Molecular and Cellular Life Sciences at Utrecht University, specializing in Biophysics & Molecular Imaging with a Bioinformatics minor profile. During my studies, I developed a strong interdisciplinary foundation combining molecular biology, quantitative analysis, and computational methods. I conducted two internships, one in wet-lab settings, and the other one in a computational environment at Karolinska Institutet, where I built and optimized an evolutionary inference pipeline to study regenerative wound healing in African spiny mice.